[R-sig-ME] warnings when using binomial models and offset (log(x))

[Joana Martelo]

Thanks for your help!

However, I still get the warnings when using offset(log(density)


> Model1<-glmer(capture~length+offset(log(density+2))+(1|fish.id.c),family=binomial,data=cap)


Warning messages:
1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
  Model failed to converge with max|grad| = 0.258231 (tol = 0.001, component 1)
2: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
  Model is nearly unidentifiable: very large eigenvalue
 - Rescale variables?


Any suggestion?

Thanks
Joana



-----Mensagem original-----
De: Mollie Brooks [mailto:mollieebrooks using gmail.com] 
Enviada: segunda-feira, 26 de Novembro de 2018 12:36
Para: Joana Martelo
Cc: R SIG Mixed Models
Assunto: Re: [R-sig-ME] warnings when using binomial models and offset - NaNs

If you’re using the scale() function to standardize your density values, you could use the argument, center=FALSE, to avoid subtracting the mean and thus avoid negative densities. 

cheers,
Mollie

> On 26Nov 2018, at 13:33, Joana Martelo <joanamartelo using gmail.com> wrote:
> 
> Thanks for your email!
> 
> Warnings' problem is solved, however, when I use log(density) or 
> log(density+1) I got NaNs because density has negative numbers. 
> Density is 2,4,6 which standardized gives -1.793073717, -0.450015136, 
> 0.893043446. So, log(-1.793073717+1)= NaN
> 
> Any suggestions?
> 
> Many thanks!
> Joana
> 
> 
> -----Mensagem original-----
> De: R-sig-mixed-models 
> [mailto:r-sig-mixed-models-bounces using r-project.org] Em nome de Ben 
> Bolker
> Enviada: sexta-feira, 23 de Novembro de 2018 21:54
> Para: r-sig-mixed-models using r-project.org
> Assunto: Re: [R-sig-ME] warnings when using binomial models and offset
> 
> 
>  This is a pretty common error, which I've now added to the GLMM FAQ.
> You should be using log(density), not density, as your offset term; if you use density, then you end up specifying that your capture counts are proportional to exp(density), which is often a ridiculously huge number.
> 
> cheers
>   Ben Bolker
> 
> On 2018-11-23 12:26 p.m., Joana Martelo wrote:
>> Hello everyone
>> 
>> 
>> 
>> I'm trying to model fish capture success using length, velocity and 
>> group composition as explanatory variables, density as an offset 
>> variable, and fish.id. as random effect. I'm getting the follow warnings:
>> 
>> 
>> 
>> Model1<-glmer(capture~length+offset(density)+(1|fish.id),family=binom
>> i
>> al,dat
>> a=cap)
>> 
>> 
>> 
>> Warning messages:
>> 
>> 1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
>> 
>>  Model failed to converge with max|grad| = 0.260123 (tol = 0.001, 
>> component
>> 1)
>> 
>> 2: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
>> 
>>  Model is nearly unidentifiable: very large eigenvalue
>> 
>> - Rescale variables?
>> 
>> 
>> 
>> 
>> 
>> -          I only get the warnings when I use length and group composition,
>> not with velocity.
>> 
>> -          I don't get any warning if I don't use the offset.
>> 
>> 
>> 
>> I've tried:
>> 
>> Model1<-glmer(capture~length+offset(log(density))+(1|fish.id.c),famil
>> y
>> =binom
>> ial(link="cloglog"),data=cap)
>> 
>> 
>> 
>> But still get the warning.
>> 
>> 
>> 
>> Any ideas of what might be the problem?
>> 
>> 
>> 
>> Many thanks!
>> 
>> 
>> 
>> 
>> 
>> Joana Martelo
>> 
>> 
>> 
>> 
>> 
>> 
>> 
>> 
>> 
>> Melhores cumprimentos,
>> 
>> 
>> 
>> Joana Martins
>> 
>> 
>> 
>> 
>> 
>> 
>> 
>> 
>> 	[[alternative HTML version deleted]]
>> 
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>> 
> 
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